Tag: Business Intelligence

Conversational AI and NLP Expand Access to Analytics

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February 25, 2026

Users LOVE Conversational AI and Intuitive Analytics

Forbes Reports that Conversational AI is making autonomous agents capable of completing end-to-end workflows, so much so that Deloitte projects that 25% of businesses using GenAI will deploy AI agents in 2025 (growing to 50% in 2027).

Analytics solutions represents an ever-expending segment for conversational AI for features and function, and the use of Natural Language Processing (NLP) and Conversational Artificial Intelligence will continue to impact the industry as end users demand easier, more intuitive ways to prepare, analyze, share and report on data.

When we consider this evolving technology, and how it will continue to affect BI solutions and augmented analytics software, one thing is clear. The average enterprise and its users will push for more intuitive products and services, for ease-of-use and improved productivity, improved user adoption, affordability, the flexibility to grow and change with new technology and with business markets.

While we cannot make specific predictions about the evolution of AI and NLP, we can predict that businesses and users will push software vendors and technology companies to provide simpler tools, better, more accurate insight and results and automated features that provide users with alerts, suggestions and support to make their jobs easier and improve results.

Incorporating conversation AI bots and NLP within BI tools will allow users to monitor and manage results more easily and optimize their time by focusing on other, more crucial tasks.

When the organization invests in new or upgraded self-serve analytical tools, it must first ensure that users will adopt these tools and that the features and analytics provided will result in increased productivity and collaboration and resource optimization. When the enterprise selects BI tools with Conversational AI and NLP features, it can achieve all of these goals and assure a good Return on Investment (ROI) and Total Cost of Ownership (TCO).

As Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies evolve, these technologies will be applied within advanced analytics, self-serve analytics and business intelligence (BI) tools to further improve features, provide better, faster insight and clearer, more concise results and optimize human resources and productivity.

Businesses and Users Push for More as Conversational AI and NLP Expands Access to Analytics

The future of AI and NLP in BI tools will support:

  • Processing large volumes of unstructured data (text, speech, written) to produce actionable insight and reports.
  • Automatically identifying trends, patterns and sentiments to alert users of changes and shifts that may affect goals.
  • Supporting decisions with conversational business intelligence to allow team members and executives to interact through NLP.
  • Real-time analytics to reveal sentiment, emotion, context and tone in customer interaction.
  • Automated reporting to save time and analyze complex data.
  • External data integration to analyze markets, social media, financial markets, investments, and other aspects of external data that will affect businesses.
  • Understanding and responding to voice commands, analyzing and working with contextual information, predicting user needs.
  • Eliminating static reporting, using conversational, dynamic analytics that can leverage predictive and analytical algorithms to produce results.

Contact Us to find out more about how your business can incorporate Artificial Intelligence (AI), natural language processing (NLP) and machine learning into your products, your business processes and your Digital Transformation (Dx) initiatives. Our AI-Enabled Advanced Analytics Solutions and Products And Services can help you achieve your vision with affordable, dependable technology. Explore our white paper ‘Conversational AI And NLP Analytics Reduces The Dependence And Usage Of Traditional BI Tools, And Improves User Adoption And Data Democratization,’ and our free articles about Agentic AI: ‘The New Age Of AI: Agentic AI’, and ‘What Is Agentic AI And Why Should I Consider It For Apps?’

Original Post : Conversational AI and NLP Expand Access to Analytics!

Smarten Support Portal Updates – January – 2026!

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February 5, 2026

We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal.

If you have not registered yet, Click Here to obtain your login credentials.

Knowledgebase Articles

  1. Datasets & Cubes : Migration from Cube to Dataset
  2. Data Sources : Improving performance for fetching data from the database
  3. Crosstab : Spot the Gross Sales highlighters

Predictive Use cases

  1. Assisted predictive modelling : Classification : Customer Churn model using Smarten Assisted Predictive Modelling
  2. Assisted predictive modelling : Hypothesis : Independent Sample T-test Using Smarten Augmented Analytics

Forum Topics

  1. Dashboards : How to improve the dashboard loading time in Smarten?
  2. Others : General : How to add SSL certificate to the Smarten BI Portal?

Manuals and Technical Guides

  1. Smarten Concept Manual SmartenInsight
  2. Smarten Working with Real time data
  3. Smarten Working with On-Premise Gateway

If you don’t find what you need in the Support Portal, we hope you will contact us with your questions, comments or suggestions. We are here to help and to support your business goals and success!

URL: Smarten Customer and Partner Community
Email: support@Smarten.com

Original Post : Smarten Support Portal Updates – January – 2026!

White Paper – Conversational AI and NLP Analytics Reduces the Dependence and Usage of Traditional BI Tools, and Improves User Adoption and Data Democratization

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January 7, 2026
White Paper – Conversational AI and NLP Analytics Reduces the Dependence and Usage of Traditional BI Tools, and Improves User Adoption and Data Democratization!

Conversational AI and NLP Analytics
Reduces the Dependence and Usage of Traditional BI Tools, and Improves User Adoption and Data Democratization

The incorporation of Artificial Intelligence (AI) and Natural Language processing (NLP) in existing business intelligence and self-serve analytics tools has had (and will continue to have) a profound influence on ease-of-use, on user adoption and on the democratization of data across the enterprise, and the use of Conversational AI and NLP is rapidly changing the face of BI tools and business user and organizational expectations.

Download White Paper

Smarten Support Portal Updates – December – 2025!

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December 30, 2025

We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal.

If you have not registered yet, Click Here to obtain your login credentials.

Knowledgebase Articles

  1. Datasets & Cubes : Data Operations
  2. GeoMap : Workflow to create Default geomap
  3. Crosstab : Making use of Cell references

Predictive Use cases

  1. Assisted predictive modelling : Medical Cost Prediction Using Smarten Assisted Predictive Modelling
  2. Assisted predictive modelling : Hypothesis : One-Way Anova test using Smarten Augmented Analytics

Business Use Cases

  1. Business Scenarios : Calculating Pending Completion Months for an Ongoing Project
  2. Business Scenarios : Find out the frequency of repetition of dimension value combinations – e.g. frequency of combination of bread and butter from sales transactions

Manuals and Technical Guides

  1. Smarten User Manual SSDP
  2. Smarten Working with Sentiment Analysis
  3. Smarten Dashboard Design Best Practices

If you don’t find what you need in the Support Portal, we hope you will contact us with your questions, comments or suggestions. We are here to help and to support your business goals and success!

URL: Smarten Customer and Partner Community
Email: support@Smarten.com

Original Post: Smarten Support Portal Updates – December – 2025!

Augmented Analytics Can Support a Large User Base

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November 7, 2025

Support Your Large Business User Base with the RIGHT BI Tools

According To Finance Online, Allied Market Research reports that small and medium businesses are driving enterprise use of analytics, but World Data Science Initiative reports that 80% of global companies are investing in data analytics, thereby revealing analytics growth across, small, medium and large enterprises.

For your large enterprise, data analytics can and will be a definitive issue impacting your business and market growth. Choosing the right solution to support data democratization and improved data literacy across the enterprise will ensure that your team can create, share, collaborate and report on data, make recommendations and suggestions based on fact, and use data-driven metrics to ensure that strategies and operational decisions are relevant, accurate and effective.

‘While many large organizations are daunted by the idea of implementing analytics across the organizations, it is completely feasible to plan for an deploy this software and to modify business processes to build on fact-based decisions.’

Today’s self-serve augmented analytics and modern business intelligence solutions are designed to support users across the enterprise, and a solution that is built on the right technology platforms, will enable rapid implementation and user adoption and requires very little training or transition time. Auto-suggestions and recommendations allow users to work on their own, no matter their skill levels.

To support a large user base, you will want to select an augmented analytics solution designed with a low-code, no-code, artificial intelligence and machine learning environment to ensure scalability and seamless, responsive, mobile access.

Contrary to Some Opinions, a Large Enterprise with Many Users CAN Adopt Augmented Analytics

Your team can untangle quality and maintenance issues, refine customer targeting and marketing optimization, make appropriate financial investment decisions, and even use external data to analyze trends and patterns and make forecasts and predications.

Real-time data management lets users connect to data sources in real time, and compiles data for fast performance to deliver real time analytics. Cached data management caches data and performs pre-aggregation and other computations for superior performance and analytics, and refreshes data from data sources at a defined frequency.

Your enterprise can choose on-premises or private or public cloud-based data management to access the analytics solution from any business location around the world, or for remote workers or those working on the road, in hotels or airports.

‘For your large enterprise, data analytics can and will be a definitive issue impacting your business and market growth. Choose the right solution to support data democratization and improved data literacy and use data-driven metrics to ensure that strategies and operational decisions are relevant, accurate and effective.’

While many large organizations are daunted by the idea of implementing analytics across the organizations, it is completely feasible to plan for an deploy this software and to modify business processes to build on fact-based decisions. Work with your IT partner to plan a reasonable roll-out and address cultural concerns, and to budget for and implement an affordable, dependable analytics solutions across the enterprise. No matter how many business users your business has, you CAN adopt and leverage self-serve augmented analytics to support your business, improve competitive advantage and gain crucial insight into data for planning, problem-solving and identification of trends, patterns, issues and opportunities.

Ensure appropriate Technology, skills and knowledge, Cutting-Edge Features and an advanced approach to Augmented Analytics And Business Intelligence. Contact Us to find out more about the Smarten suite of products. Explore our free white paper: ‘Enabling Business Optimization And Expense Reduction Through The Use Of Augmented Analytics.’

Original Post : Augmented Analytics Can Support a Large User Base!

Smarten Support Portal Updates – October – 2025!

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October 31, 2025

We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal.

If you have not registered yet, Click Here to obtain your login credentials.

Knowledgebase Articles

  1. Crosstab : Spot the Gross Sales highlighters
  2. Data Sources : Improve data extraction performance from database data source
  3. Datasets & Cubes : Manage columns while creating dataset

Predictive Use cases

  1. Assisted predictive modelling : Classification : Customer Churn model using Smarten Assisted Predictive Modelling
  2. Assisted predictive modelling : Hypothesis : Independent Sample T-test Using Smarten Augmented Analytics

Forum Topics

  1. Embedded / API Integration : How to rebuild cubes/ datasets through API call ?
  2. Graphs : Global Variable : How can I plot the dynamic graph based on measure selected from the list of measures

Manuals and Technical Guides

  1. Smarten Concept Manual BI
  2. Smarten Concept Manual SmartenInsight
  3. Smarten Working with Multitenancy

If you don’t find what you need in the Support Portal, we hope you will contact us with your questions, comments or suggestions. We are here to help and to support your business goals and success!

URL: Smarten Customer and Partner Community
Email: support@Smarten.com

Original Post: Smarten Support Portal Updates – October – 2025!

What Are Citizen Data Scientists Doing Today?

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October 29, 2025

How Has the Citizen Data Scientist Role Evolved?

Ten years ago, the term ‘Citizen Data Scientist’ was coined by the world-renowned technology research firm, Gartner. The term refers to business team members whose expertise and role are not focused on analytics as a primary job function. Using self-serve analytics solutions, these team members can leverage analytics to create models, reports and analysis to collaborate, share and make decisions. Gartner predicted the emergence of this role within businesses as part of the growing importance of data analytics and data-driven decisions within the business environment.

A decade later, it is worth reviewing the status of this role in the business enterprise and within the average organization. Is the Citizen Data Scientist role a standard role within most businesses today? Does a Citizen Data Scientist replace or work independently from a Data Scientist or Business Analyst? Has the Gartner prediction come to fruition?

While there are no current statistics regarding the number of companies currently using a Citizen Data Scientist approach, the trend toward data-driven planning and forecasting is clear. As with many other business trends, the larger organizations usually take the lead. They have the budget and the depth of resources to plan for and deploy changes across the enterprise and to test theories and enforce cultural changes.

Here are some statistics that reflect the growth of the Citizen Data Scientist movement and the supporting technologies that engender this approach:

After Ten Years, Is the Promise of Citizen Data Scientists Fulfilled?
  • Studies reveal that the number of Citizen Data Scientists is growing five times faster than the number of Data Scientists.
  • Automation technologies support the growth of the Citizen Data Scientist approach with over 40% of data science tasks automated through augmented analytics and/or machine learning.
  • The Machine Learning (ML) market is growing at a compounded annual rate of more than 15%, reflecting the need for data analytics capabilities within self-serve solutions.
  • By some estimates, interest in the Citizen Data Scientist role has tripled in the past decade, as medium and small enterprises embrace new, intuitive, more affordable technologies to support the Citizen Data Scientist concept within their organization.

As this concept became mainstream, the industries saw a trend toward increasing data-driven insight while reducing dependence on Data Scientists.

While the Citizen Data Scientist role began as a basic initiative to gather data and create simple reports, today’s Citizen Data Scientists are now using business intelligence (BI) tools and augmented analytics with Natural Language Processing (NLP), machine learning, low-code and no-code platforms and other technologies to leverage limited technical skills and create sophisticated analytics with clear results. Reports, dashboards and data sharing allow team members to create and use data models and to increase data literacy and data democratization.

Team members can use smart data visualization and assisted predictive modeling to gain insight and solve day-to-day problems, advise management and collaborate with other team members to understand trends, patterns, challenges, and opportunities and leverage metrics to make fact-based decisions.

This evolution of the Citizen Data Scientist role within the organization can free Data Scientists to perform more strategic activities without the daily distraction of simple report requests. If and when a particular data model or analytical approach must be refined to be more strategic, the Citizen Data Scientist can work with the Data Scientist to achieve that goal.

Using this approach, the enterprise can empower team members with the tools to analyze data and to use their knowledge of the industry, market, customers and business environment to make decisions and improve results.

When we consider the last decade of Citizen Data Scientist evolution, we see that businesses across all industries are working toward a more data-driven approach to decision-making, and embracing data democracy as a means to improve productivity and the quality of decisions and to reduce re-work and missteps.

Contact Us to discuss your analytical needs and to find out more about Citizen Data Scientists, and the process of choosing the right Analytics Solution for your business. Explore our free White Papers: ‘The Potential Of The Citizen Data Scientist Approach And Augmented Analytics,’ ‘Enabling Business Optimization And Expense Reduction Through The Use Of Augmented Analytics,’ and ‘A Roadmap To ROI And User Adoption Of Augmented Analytics And BI Tools.’

Original Post : What Are Citizen Data Scientists Doing Today?

Smarten Support Portal Updates – September – 2025!

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October 3, 2025

We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal.

If you have not registered yet, Click Here to obtain your login credentials.

Knowledgebase Articles

  1. General : Global Variables : Making use of Global variables
  2. Crosstab : Summary on Crosstab with multiple Row and Column dimensions
  3. Access Rights, Roles and Permissions : AD Integration in Smarten
  4. Datasets & Cubes : Handling multiple JOINs through Step by Step Procedure to create a dataset

Predictive Use cases

  1. Assisted predictive modelling : Regression : Handling Outliers Using Smarten Assisted Predictive Modelling
  2. Assisted predictive modelling : Hypothesis : One-Way Anova test using Smarten Augmented Analytics

Business Use Cases

  1. Business Scenarios : Sales Analysis Report by YoY Performance with Flexible Date Selection
  2. Business Scenarios : Calculation of Working Days Excluding Plant-Specific Holidays and Sundays

Manuals and Technical Guides

  1. Smarten Concept Manual Smartenview
  2. Smarten Concept Manual SnapShot
  3. Smarten Integration With Your App

If you don’t find what you need in the Support Portal, we hope you will contact us with your questions, comments or suggestions. We are here to help and to support your business goals and success!

URL: Smarten Customer and Partner Community
Email: support@Smarten.com

Original Post: Smarten Support Portal Updates – September – 2025!

Smarten Support Portal Updates – July – 2025!

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August 1, 2025

We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal.

If you have not registered yet, Click Here to obtain your login credentials.

Knowledgebase Articles

  1. Data Sources : Adding a new JDBC/ODBC Database Driver/Connector to Smarten
  2. Visualizations : Making use of Case statements (IfCase, When-Then)
  3. Administrator : Enable Managed Memory In Objects

Predictive Use cases

  1. Assisted predictive modelling : Classification : Customer Churn model using Smarten Assisted Predictive Modelling
  2. Assisted predictive modelling : Regression : Sampling Data using Smarten Augmented Analytics

Business Use Cases

  1. Business Scenarios : Calculating Pending Completion Months for an Ongoing Project
  2. Business Scenarios : Derive monthly closing balance of various items from yearly opening balance and their monthly transactions data

Manuals and Technical Guides

  1. Smarten Concept Manual SmartenInsight
  2. Smarten SSDP Best Practices
  3. Smarten Working with Reports

If you don’t find what you need in the Support Portal, we hope you will contact us with your questions, comments or suggestions. We are here to help and to support your business goals and success!

URL: Smarten Customer and Partner Community
Email: support@Smarten.com

Original Post: Smarten Support Portal Updates – July – 2025!

Look to Cross-Tab and Tabular Analytical BI Tools for Clear Results

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July 9, 2025

Cross-Tab and Tabular Reporting Tools Are Foundational!

The evolution of advanced analytics has been rapid and impressive. With features that provide support for business users and help to transition them into Citizen Data Scientists, and the addition of Artificial Intelligence (AI) and other capabilities like Natural Language Processing (NLP) and search analytics, augmented analytics is suitable for every team member in your organization. It is easy to be impressed with all of the new bells and whistles and these additions certainly do make a user’s life easier and help the organization to analyze and use data in a more meaningful way.

But while we are admiring these new BI tools and analytics features and technologies, we should give equal respect to the bread and butter of the business intelligence (BI) and analytical landscape! Foundational, comprehensive visualization techniques are not only meaningful, they are mandatory.

‘With flexible views and report formats and interactive features and presentation capabilities, your business users, managers, IT team and data scientists can leverage data across disparate data structures and view and present that data with intuitive formats for fact-based decision-making.’

Analytics and business intelligence (BI) tools provide many such options including:

Cross-Tab – Cross-tabulation analysis (or crosstabs), analyzes and categorizes data to reveal the relationship between two or more variables to help you make sense of survey results, reveal actionable tasks, find patterns and correlations. Cross-tab analytics can be used for categorical variables (with independent or dependent variables), for contingency tables, marginal totals, or conditional frequencies, and many other purposes.

Tabular – Tabular visualization facilitates quick comparison of data in a tabular form, marrying data classification with data presentation to reveal measures and averages in a structured format that is easy to manipulate, compare and understand. Tabular analytics can be used for statistical analysis or units of measure among other uses.

According to research at the University of North Carolina (UNC), cross-tab and tabular analytics account for 90% of the analytical techniques used in all research analysis.

A BI reporting tool that enables users to customize their view and approach and is easy to understand and use will make the user more productive and ensure Return on Investment (ROI).

Analytics Can Be Flashy, But Traditional Cross-Tab and Tabular Visualization is Your Bread and Butter

These foundational analytical visualization techniques are easy to understand and use and are suitable for business users and all team members. When you choose a Business Intelligence reporting tool that enables report, template and document design and configuration and supports preprinted fixed formats too. With flexible views and report formats and interactive features and presentation capabilities, your business users, managers, IT team and data scientists can leverage data across disparate data structures and view and present that data with intuitive formats for fact-based decision-making. IT team members or consultants can leverage a simple, basic programming or scripting environment to define format templates and use data from Datasets and objects to produce stunning pixel perfect reports. Users can preview reports, export data to PDF files and share documents and reports via email at predefined frequency using delivery and publishing agents.

‘While we are admiring new BI tools, features and technologies, we should give equal respect to the bread and butter of the business intelligence (BI) and analytical landscape! Foundational, comprehensive visualization techniques are not only meaningful, they are mandatory.’

To learn more about Traditional BI Tools And Visualization Techniques and the promise of augmented analytics and Advanced Reporting Tools, contact us now. Find out how to  ensure Return on Investment (ROI) and Total Cost of Ownership (TCO) results, gain a competitive market advantage, and enable user adoption, read our free White Paper, ‘A Roadmap To ROI And User Adoption Of Augmented Analytics And BI.’ Explore The Benefits of our Augmented Analytics And BI Tools, Contact Us. Keep pace with changing enterprise needs and support business agility. Let us help you realize your business goals and objectives with fact-based information, and flexible, scalable technology solutions that will support Citizen Data Scientist initiatives, and improved data literacy and data democratization.

Original Post: Look to Cross-Tab and Tabular Analytical BI Tools for Clear Results!